Alex Bocharov

Senior Research Software Design Engineer, Machine Learning and Applied Statistics, Microsoft Research

E-mail: alexeib@microsoft.com ; Alexei.Bocharov@microsoft.com
Mail: c/o Microsoft Corp., One Microsoft Way, Bldg. 113, Redmond WA 98052-6399, USA

My other portrait

Oportrait

(This is a two-sided iso-area mask, made out of single traditional 6” Origami square. One side is my portrait as a young man – the other side is my portrait now. Published with a kind permission of my wife Ludmila.)

Background and Research Activities

I am passionate about all kinds of mathematical algorithms. My background is in pure mathematics, but I had been active in mathematical software development and publishing for more than 10 years before joining Microsoft.

After working for more than five years on the core Algebra and Calculus features of Mathematica® (http://www.wolfram.com) I went on to work as a principal contractor developing an algebraic application that has been subsequently published as firmware for Casio® Algebra FX scientific calculator and Casio® ClassPad 300 (http://www.calculatorsinc.com/casio/classpad.HTML).

There is a lot of my code implementing both symbolic and numeric math running commercially.

My current projects are in the areas of Keyword Analysis, Adversarial Problems (spam, phishing) and Data Mining.

Data Mining Resources

The following paper on stability of time series forecasting has been presented at Data Mining and Information Engineering 2006 Conference and published in the Proceedings (“Data Mining VII”, WIT Press, 2006, pp.141 – 150)

Stability Analysis of Time Series Forecasting with ART Models

Alexei Bocharov, David Chickering, David Heckerman

Abstract.

In technical terms the cases of long range forecasting instability are characterized by rapid growth of mean absolute prediction error with time, which may or may not be accompanied by significant growth of predicted standard deviation. In practice the cases of instability where predict StDev stays tame are especially misleading, since they can furnish unreliable predictions with little or no visual cues that would characterize them as unreliable. The method described in the paper is designed to detect and control the long range forecasting instabilities and to cull the unreliable predictions.

A 2005 Data Mining overview is available here.

Abstract.

[February 2005]

Data Mining Reloaded
What's new for data mining in SQL Server 2005 Analysis Services

Alexei Bocharov,
Jesper Lind
SQL Server Magazine

The two main functions of data mining are classification and prediction (or forecasting). Data mining helps you make sense of those countless gigabytes of raw data stored in databases by finding important patterns and rules present in the data or derived from it. Analysts then use this knowledge to make predictions and recommendations about new or future data. The main business applications of data mining are learning who your customers are and what they need, understanding where the sales are coming from and what factors affect them, fashioning marketing strategies, and predicting future business indicators.

With the release of SQL Server 2000, Microsoft rebranded OLAP Services as Analysis Services to reflect the addition of newly developed data-mining capabilities. The data-mining toolset in SQL Server 2000 included only two classical analysis algorithms (Clustering and Decision Trees), a special-purpose data-mining management and query-expression language named DMX, and limited client-side controls, viewers, and development tools.

SQL Server 2005 Analysis Services comes with a greatly expanded set of data-mining methods and an array of completely new client-side analysis and development tools designed to cover most common business intelligence (BI) needs. The Business Intelligence Framework in SQL Server 2005 offers a new data-mining experience for analysts and developers alike.

A version of this paper has been reprinted as a part of A Jump Start to SQL Server BI book.

SQL Data Mining Portal

A wealth of Data Mining news briefs, tutorials, scenarios discussions and tips are being posted at the ever-expanding http://www.sqlserverdatamining.com.

Whales

No, I am not a “Save the Whales” activist (yet) – I simply like and admire the whales. Some pictures are available through either of the links below (but prepare for a 40MB download).